{"id":"W2768665845","doi":"","title":"A Watershed for Our Proceedings: Thanking Arden Ogg, Managing editor, and Chris Wolfart, Academic editor","year":2008,"lang":"en","type":"article","venue":"Algonquian Papers - Archive","topic":"Academic Publishing and Open Access","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Library science; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002211219,0.000390495,0.0005671839,0.0003837369,0.001001902,0.0006189555,0.002382739,0.000260569,0.00002542705],"category_scores_gemma":[0.003188068,0.000297586,0.0001588186,0.0004546151,0.0002610917,0.001729604,0.000721676,0.001004413,0.00004173706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008574349,"about_ca_system_score_gemma":0.0002695458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001329846,"about_ca_topic_score_gemma":0.0002884982,"domain_scores_codex":[0.9952626,0.00008914792,0.0008344816,0.00119323,0.001697227,0.0009233631],"domain_scores_gemma":[0.9973877,0.001144975,0.0004605446,0.0003550171,0.00021304,0.0004387439],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001134297,0.00001224789,0.009399316,0.00002008961,0.0000545,0.00001176177,0.008426912,0.00001197172,0.000871483,0.0001761027,0.9666204,0.01428173],"study_design_scores_gemma":[0.001232682,0.0001169278,0.008573335,0.0001376814,0.00005054692,0.00009745886,0.01981047,0.002082969,0.0005657309,0.01116384,0.9554622,0.0007062214],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7663481,0.001620341,0.003669539,0.06356793,0.06910425,0.004562882,0.0006070378,0.0008527141,0.08966725],"genre_scores_gemma":[0.9348247,0.0003843683,0.002922575,0.002783963,0.05310229,0.0001737584,0.00004668404,0.00007998154,0.00568167],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1684766,"threshold_uncertainty_score":0.9999476,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05006974187250168,"score_gpt":0.342380764662845,"score_spread":0.2923110227903433,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}